Flow Nexus Swarm

by ruvnet60de638630abNo license74K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

Instructions onlyAI & Agents DevOps & Cloud

AI-generated overview

Deploy and orchestrate cloud-based AI agent swarms and event-driven workflows on the Flow Nexus platform.

What it does: This skill documents how to use Flow Nexus MCP tools to initialize AI agent swarms with topologies such as hierarchical, mesh, ring, and star, and to spawn specialized agents. It covers creating and executing event-driven workflows with dependency management, parallel steps, triggers, and retry policies, plus monitoring, scaling, and destroying swarms. It also provides reusable patterns and templates for full-stack development, research, CI/CD, and data processing pipelines.
When to use it: Use it when coordinating multiple AI agents on a cloud platform, such as running parallel research, multi-repo development, or automated deployment pipelines. It fits projects that need event-driven workflow automation, message queue processing, or scalable agent orchestration.
Requirements: Requires the Flow Nexus MCP server, installed via npm and registered with an account, plus network access to the Flow Nexus cloud platform. The skill ships no scripts; it contains instructions and MCP tool call examples only.

Flow Nexus Swarm & Workflow Orchestration

Deploy and manage cloud-based AI agent swarms with event-driven workflow automation, message queue processing, and intelligent agent coordination.

Overview

Flow Nexus provides cloud-based orchestration for AI agent swarms with:

Multi-topology Support: Hierarchical, mesh, ring, and star architectures
Event-driven Workflows: Message queue processing with async execution
Template Library: Pre-built swarm configurations for common use cases
Intelligent Agent Assignment: Vector similarity matching for optimal agent selection
Real-time Monitoring: Comprehensive metrics and audit trails
Scalable Infrastructure: Cloud-based execution with auto-scaling

Swarm Management

Initialize Swarm

Create a new swarm with specified topology and configuration:

javascript

mcp__flow-nexus__swarm_init({  topology: "hierarchical", // Options: mesh, ring, star, hierarchical  maxAgents: 8,  strategy: "balanced" // Options: balanced, specialized, adaptive})

mcp__flow-nexus__swarm_init({  topology: "hierarchical", // Options: mesh, ring, star, hierarchical  maxAgents: 8,  strategy: "balanced" // Options: balanced, specialized, adaptive})

Topology Guide:

Hierarchical: Tree structure with coordinator nodes (best for complex projects)
Mesh: Peer-to-peer collaboration (best for research and analysis)
Ring: Circular coordination (best for sequential workflows)
Star: Centralized hub (best for simple delegation)

Strategy Guide:

Balanced: Equal distribution of workload across agents
Specialized: Agents focus on specific expertise areas
Adaptive: Dynamic adjustment based on task complexity

Spawn Agents

Add specialized agents to the swarm:

javascript

mcp__flow-nexus__agent_spawn({  type: "researcher", // Options: researcher, coder, analyst, optimizer, coordinator  name: "Lead Researcher",  capabilities: ["web_search", "analysis", "summarization"]})

mcp__flow-nexus__agent_spawn({  type: "researcher", // Options: researcher, coder, analyst, optimizer, coordinator  name: "Lead Researcher",  capabilities: ["web_search", "analysis", "summarization"]})

Agent Types:

Researcher: Information gathering, web search, analysis
Coder: Code generation, refactoring, implementation
Analyst: Data analysis, pattern recognition, insights
Optimizer: Performance tuning, resource optimization
Coordinator: Task delegation, progress tracking, integration

Orchestrate Tasks

Distribute tasks across the swarm:

javascript

mcp__flow-nexus__task_orchestrate({  task: "Build a REST API with authentication and database integration",  strategy: "parallel", // Options: parallel, sequential, adaptive  maxAgents: 5,  priority: "high" // Options: low, medium, high, critical})

mcp__flow-nexus__task_orchestrate({  task: "Build a REST API with authentication and database integration",  strategy: "parallel", // Options: parallel, sequential, adaptive  maxAgents: 5,  priority: "high" // Options: low, medium, high, critical})

Execution Strategies:

Parallel: Maximum concurrency for independent subtasks
Sequential: Step-by-step execution with dependencies
Adaptive: AI-powered strategy selection based on task analysis

Monitor & Scale Swarms

javascript

// Get detailed swarm statusmcp__flow-nexus__swarm_status({  swarm_id: "optional-id" // Uses active swarm if not provided})
// List all active swarmsmcp__flow-nexus__swarm_list({  status: "active" // Options: active, destroyed, all})
// Scale swarm up or downmcp__flow-nexus__swarm_scale({  target_agents: 10,  swarm_id: "optional-id"})
// Gracefully destroy swarmmcp__flow-nexus__swarm_destroy({  swarm_id: "optional-id"})

// Get detailed swarm statusmcp__flow-nexus__swarm_status({  swarm_id: "optional-id" // Uses active swarm if not provided})
// List all active swarmsmcp__flow-nexus__swarm_list({  status: "active" // Options: active, destroyed, all})
// Scale swarm up or downmcp__flow-nexus__swarm_scale({  target_agents: 10,  swarm_id: "optional-id"})
// Gracefully destroy swarmmcp__flow-nexus__swarm_destroy({  swarm_id: "optional-id"})

Workflow Automation

Create Workflow

Define event-driven workflows with message queue processing:

javascript

mcp__flow-nexus__workflow_create({  name: "CI/CD Pipeline",  description: "Automated testing, building, and deployment",  steps: [    {      id: "test",      action: "run_tests",      agent: "tester",      parallel: true    },    {      id: "build",      action: "build_app",      agent: "builder",      depends_on: ["test"]    },    {      id: "deploy",      action: "deploy_prod",      agent: "deployer",      depends_on: ["build"]    }  ],  triggers: ["push_to_main", "manual_trigger"],  metadata: {    priority: 10,    retry_policy: "exponential_backoff"  }})

mcp__flow-nexus__workflow_create({  name: "CI/CD Pipeline",  description: "Automated testing, building, and deployment",  steps: [    {      id: "test",      action: "run_tests",      agent: "tester",      parallel: true    },    {      id: "build",      action: "build_app",      agent: "builder",      depends_on: ["test"]    },    {      id: "deploy",      action: "deploy_prod",      agent: "deployer",      depends_on: ["build"]    }  ],  triggers: ["push_to_main", "manual_trigger"],  metadata: {    priority: 10,    retry_policy: "exponential_backoff"  }})

Workflow Features:

Dependency Management: Define step dependencies with depends_on
Parallel Execution: Set parallel: true for concurrent steps
Event Triggers: GitHub events, schedules, manual triggers
Retry Policies: Automatic retry on transient failures
Priority Queuing: High-priority workflows execute first

Execute Workflow

Run workflows synchronously or asynchronously:

javascript

mcp__flow-nexus__workflow_execute({  workflow_id: "workflow_id",  input_data: {    branch: "main",    commit: "abc123",    environment: "production"  },  async: true // Queue-based execution for long-running workflows})

mcp__flow-nexus__workflow_execute({  workflow_id: "workflow_id",  input_data: {    branch: "main",    commit: "abc123",    environment: "production"  },  async: true // Queue-based execution for long-running workflows})

Execution Modes:

Sync (async: false): Immediate execution, wait for completion
Async (async: true): Message queue processing, non-blocking

Monitor Workflows

javascript

// Get workflow status and metricsmcp__flow-nexus__workflow_status({  workflow_id: "id",  execution_id: "specific-run-id", // Optional  include_metrics: true})
// List workflows with filtersmcp__flow-nexus__workflow_list({  status: "running", // Options: running, completed, failed, pending  limit: 10,  offset: 0})
// Get complete audit trailmcp__flow-nexus__workflow_audit_trail({  workflow_id: "id",  limit: 50,  start_time: "2025-01-01T00:00:00Z"})

// Get workflow status and metricsmcp__flow-nexus__workflow_status({  workflow_id: "id",  execution_id: "specific-run-id", // Optional  include_metrics: true})
// List workflows with filtersmcp__flow-nexus__workflow_list({  status: "running", // Options: running, completed, failed, pending  limit: 10,  offset: 0})
// Get complete audit trailmcp__flow-nexus__workflow_audit_trail({  workflow_id: "id",  limit: 50,  start_time: "2025-01-01T00:00:00Z"})

Agent Assignment

Intelligently assign agents to workflow tasks:

javascript

mcp__flow-nexus__workflow_agent_assign({  task_id: "task_id",  agent_type: "coder", // Preferred agent type  use_vector_similarity: true // AI-powered capability matching})

mcp__flow-nexus__workflow_agent_assign({  task_id: "task_id",  agent_type: "coder", // Preferred agent type  use_vector_similarity: true // AI-powered capability matching})

Vector Similarity Matching:

Analyzes task requirements and agent capabilities
Finds optimal agent based on past performance
Considers workload and availability

Queue Management

Monitor and manage message queues:

javascript

mcp__flow-nexus__workflow_queue_status({  queue_name: "optional-specific-queue",  include_messages: true // Show pending messages})

mcp__flow-nexus__workflow_queue_status({  queue_name: "optional-specific-queue",  include_messages: true // Show pending messages})

Agent Orchestration

Full-Stack Development Pattern

javascript

// 1. Initialize swarm with hierarchical topologymcp__flow-nexus__swarm_init({  topology: "hierarchical",  maxAgents: 8,  strategy: "specialized"})
// 2. Spawn specialized agentsmcp__flow-nexus__agent_spawn({ type: "coordinator", name: "Project Manager" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Backend Developer" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Frontend Developer" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Database Architect" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "QA Engineer" })
// 3. Create development workflowmcp__flow-nexus__workflow_create({  name: "Full-Stack Development",  steps: [    { id: "requirements", action: "analyze_requirements", agent: "coordinator" },    { id: "db_design", action: "design_schema", agent: "Database Architect" },    { id: "backend", action: "build_api", agent: "Backend Developer", depends_on: ["db_design"] },    { id: "frontend", action: "build_ui", agent: "Frontend Developer", depends_on: ["requirements"] },    { id: "integration", action: "integrate", agent: "Backend Developer", depends_on: ["backend", "frontend"] },    { id: "testing", action: "qa_testing", agent: "QA Engineer", depends_on: ["integration"] }  ]})
// 4. Execute workflowmcp__flow-nexus__workflow_execute({  workflow_id: "workflow_id",  input_data: {    project: "E-commerce Platform",    tech_stack: ["Node.js", "React", "PostgreSQL"]  }})

// 1. Initialize swarm with hierarchical topologymcp__flow-nexus__swarm_init({  topology: "hierarchical",  maxAgents: 8,  strategy: "specialized"})
// 2. Spawn specialized agentsmcp__flow-nexus__agent_spawn({ type: "coordinator", name: "Project Manager" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Backend Developer" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Frontend Developer" })mcp__flow-nexus__agent_spawn({ type: "coder", name: "Database Architect" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "QA Engineer" })
// 3. Create development workflowmcp__flow-nexus__workflow_create({  name: "Full-Stack Development",  steps: [    { id: "requirements", action: "analyze_requirements", agent: "coordinator" },    { id: "db_design", action: "design_schema", agent: "Database Architect" },    { id: "backend", action: "build_api", agent: "Backend Developer", depends_on: ["db_design"] },    { id: "frontend", action: "build_ui", agent: "Frontend Developer", depends_on: ["requirements"] },    { id: "integration", action: "integrate", agent: "Backend Developer", depends_on: ["backend", "frontend"] },    { id: "testing", action: "qa_testing", agent: "QA Engineer", depends_on: ["integration"] }  ]})
// 4. Execute workflowmcp__flow-nexus__workflow_execute({  workflow_id: "workflow_id",  input_data: {    project: "E-commerce Platform",    tech_stack: ["Node.js", "React", "PostgreSQL"]  }})

Research & Analysis Pattern

javascript

// 1. Initialize mesh topology for collaborative researchmcp__flow-nexus__swarm_init({  topology: "mesh",  maxAgents: 5,  strategy: "balanced"})
// 2. Spawn research agentsmcp__flow-nexus__agent_spawn({ type: "researcher", name: "Primary Researcher" })mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Secondary Researcher" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Data Analyst" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Insights Analyst" })
// 3. Orchestrate research taskmcp__flow-nexus__task_orchestrate({  task: "Research machine learning trends for 2025 and analyze market opportunities",  strategy: "parallel",  maxAgents: 4,  priority: "high"})

// 1. Initialize mesh topology for collaborative researchmcp__flow-nexus__swarm_init({  topology: "mesh",  maxAgents: 5,  strategy: "balanced"})
// 2. Spawn research agentsmcp__flow-nexus__agent_spawn({ type: "researcher", name: "Primary Researcher" })mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Secondary Researcher" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Data Analyst" })mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Insights Analyst" })
// 3. Orchestrate research taskmcp__flow-nexus__task_orchestrate({  task: "Research machine learning trends for 2025 and analyze market opportunities",  strategy: "parallel",  maxAgents: 4,  priority: "high"})

CI/CD Pipeline Pattern

javascript

mcp__flow-nexus__workflow_create({  name: "Deployment Pipeline",  description: "Automated testing, building, and multi-environment deployment",  steps: [    { id: "lint", action: "lint_code", agent: "code_quality", parallel: true },    { id: "unit_test", action: "unit_tests", agent: "test_runner", parallel: true },    { id: "integration_test", action: "integration_tests", agent: "test_runner", parallel: true },    { id: "build", action: "build_artifacts", agent: "builder", depends_on: ["lint", "unit_test", "integration_test"] },    { id: "security_scan", action: "security_scan", agent: "security", depends_on: ["build"] },    { id: "deploy_staging", action: "deploy", agent: "deployer", depends_on: ["security_scan"] },    { id: "smoke_test", action: "smoke_tests", agent: "test_runner", depends_on: ["deploy_staging"] },    { id: "deploy_prod", action: "deploy", agent: "deployer", depends_on: ["smoke_test"] }  ],  triggers: ["github_push", "github_pr_merged"],  metadata: {    priority: 10,    auto_rollback: true  }})

mcp__flow-nexus__workflow_create({  name: "Deployment Pipeline",  description: "Automated testing, building, and multi-environment deployment",  steps: [    { id: "lint", action: "lint_code", agent: "code_quality", parallel: true },    { id: "unit_test", action: "unit_tests", agent: "test_runner", parallel: true },    { id: "integration_test", action: "integration_tests", agent: "test_runner", parallel: true },    { id: "build", action: "build_artifacts", agent: "builder", depends_on: ["lint", "unit_test", "integration_test"] },    { id: "security_scan", action: "security_scan", agent: "security", depends_on: ["build"] },    { id: "deploy_staging", action: "deploy", agent: "deployer", depends_on: ["security_scan"] },    { id: "smoke_test", action: "smoke_tests", agent: "test_runner", depends_on: ["deploy_staging"] },    { id: "deploy_prod", action: "deploy", agent: "deployer", depends_on: ["smoke_test"] }  ],  triggers: ["github_push", "github_pr_merged"],  metadata: {    priority: 10,    auto_rollback: true  }})

Data Processing Pipeline Pattern

javascript

mcp__flow-nexus__workflow_create({  name: "ETL Pipeline",  description: "Extract, Transform, Load data processing",  steps: [    { id: "extract", action: "extract_data", agent: "data_extractor" },    { id: "validate_raw", action: "validate_data", agent: "validator", depends_on: ["extract"] },    { id: "transform", action: "transform_data", agent: "transformer", depends_on: ["validate_raw"] },    { id: "enrich", action: "enrich_data", agent: "enricher", depends_on: ["transform"] },    { id: "load", action: "load_data", agent: "loader", depends_on: ["enrich"] },    { id: "validate_final", action: "validate_data", agent: "validator", depends_on: ["load"] }  ],  triggers: ["schedule:0 2 * * *"], // Daily at 2 AM  metadata: {    retry_policy: "exponential_backoff",    max_retries: 3  }})

mcp__flow-nexus__workflow_create({  name: "ETL Pipeline",  description: "Extract, Transform, Load data processing",  steps: [    { id: "extract", action: "extract_data", agent: "data_extractor" },    { id: "validate_raw", action: "validate_data", agent: "validator", depends_on: ["extract"] },    { id: "transform", action: "transform_data", agent: "transformer", depends_on: ["validate_raw"] },    { id: "enrich", action: "enrich_data", agent: "enricher", depends_on: ["transform"] },    { id: "load", action: "load_data", agent: "loader", depends_on: ["enrich"] },    { id: "validate_final", action: "validate_data", agent: "validator", depends_on: ["load"] }  ],  triggers: ["schedule:0 2 * * *"], // Daily at 2 AM  metadata: {    retry_policy: "exponential_backoff",    max_retries: 3  }})

Templates & Patterns

Use Pre-built Templates

javascript

// Create swarm from templatemcp__flow-nexus__swarm_create_from_template({  template_name: "full-stack-dev",  overrides: {    maxAgents: 6,    strategy: "specialized"  }})
// List available templatesmcp__flow-nexus__swarm_templates_list({  category: "quickstart", // Options: quickstart, specialized, enterprise, custom, all  includeStore: true})

// Create swarm from templatemcp__flow-nexus__swarm_create_from_template({  template_name: "full-stack-dev",  overrides: {    maxAgents: 6,    strategy: "specialized"  }})
// List available templatesmcp__flow-nexus__swarm_templates_list({  category: "quickstart", // Options: quickstart, specialized, enterprise, custom, all  includeStore: true})

Available Template Categories:

Quickstart Templates:

full-stack-dev: Complete web development swarm
research-team: Research and analysis swarm
code-review: Automated code review swarm
data-pipeline: ETL and data processing

Specialized Templates:

ml-development: Machine learning project swarm
mobile-dev: Mobile app development
devops-automation: Infrastructure and deployment
security-audit: Security analysis and testing

Enterprise Templates:

enterprise-migration: Large-scale system migration
multi-repo-sync: Multi-repository coordination
compliance-review: Regulatory compliance workflows
incident-response: Automated incident management

Custom Template Creation

Save successful swarm configurations as reusable templates for future projects.

Advanced Features

Real-time Monitoring

javascript

// Subscribe to execution streamsmcp__flow-nexus__execution_stream_subscribe({  stream_type: "claude-flow-swarm",  deployment_id: "deployment_id"})
// Get execution statusmcp__flow-nexus__execution_stream_status({  stream_id: "stream_id"})
// List files created during executionmcp__flow-nexus__execution_files_list({  stream_id: "stream_id",  created_by: "claude-flow"})

// Subscribe to execution streamsmcp__flow-nexus__execution_stream_subscribe({  stream_type: "claude-flow-swarm",  deployment_id: "deployment_id"})
// Get execution statusmcp__flow-nexus__execution_stream_status({  stream_id: "stream_id"})
// List files created during executionmcp__flow-nexus__execution_files_list({  stream_id: "stream_id",  created_by: "claude-flow"})

Swarm Metrics & Analytics

javascript

// Get swarm performance metricsmcp__flow-nexus__swarm_status({  swarm_id: "id"})
// Analyze workflow efficiencymcp__flow-nexus__workflow_status({  workflow_id: "id",  include_metrics: true})

// Get swarm performance metricsmcp__flow-nexus__swarm_status({  swarm_id: "id"})
// Analyze workflow efficiencymcp__flow-nexus__workflow_status({  workflow_id: "id",  include_metrics: true})

Multi-Swarm Coordination

Coordinate multiple swarms for complex, multi-phase projects:

javascript

// Phase 1: Research swarmconst researchSwarm = await mcp__flow-nexus__swarm_init({  topology: "mesh",  maxAgents: 4})
// Phase 2: Development swarmconst devSwarm = await mcp__flow-nexus__swarm_init({  topology: "hierarchical",  maxAgents: 8})
// Phase 3: Testing swarmconst testSwarm = await mcp__flow-nexus__swarm_init({  topology: "star",  maxAgents: 5})

// Phase 1: Research swarmconst researchSwarm = await mcp__flow-nexus__swarm_init({  topology: "mesh",  maxAgents: 4})
// Phase 2: Development swarmconst devSwarm = await mcp__flow-nexus__swarm_init({  topology: "hierarchical",  maxAgents: 8})
// Phase 3: Testing swarmconst testSwarm = await mcp__flow-nexus__swarm_init({  topology: "star",  maxAgents: 5})

Best Practices

1. Choose the Right Topology

javascript

// Simple projects: Starmcp__flow-nexus__swarm_init({ topology: "star", maxAgents: 3 })
// Collaborative work: Meshmcp__flow-nexus__swarm_init({ topology: "mesh", maxAgents: 5 })
// Complex projects: Hierarchicalmcp__flow-nexus__swarm_init({ topology: "hierarchical", maxAgents: 10 })
// Sequential workflows: Ringmcp__flow-nexus__swarm_init({ topology: "ring", maxAgents: 4 })

// Simple projects: Starmcp__flow-nexus__swarm_init({ topology: "star", maxAgents: 3 })
// Collaborative work: Meshmcp__flow-nexus__swarm_init({ topology: "mesh", maxAgents: 5 })
// Complex projects: Hierarchicalmcp__flow-nexus__swarm_init({ topology: "hierarchical", maxAgents: 10 })
// Sequential workflows: Ringmcp__flow-nexus__swarm_init({ topology: "ring", maxAgents: 4 })

2. Optimize Agent Assignment

javascript

// Use vector similarity for optimal matchingmcp__flow-nexus__workflow_agent_assign({  task_id: "complex-task",  use_vector_similarity: true})

// Use vector similarity for optimal matchingmcp__flow-nexus__workflow_agent_assign({  task_id: "complex-task",  use_vector_similarity: true})

3. Implement Proper Error Handling

javascript

mcp__flow-nexus__workflow_create({  name: "Resilient Workflow",  steps: [...],  metadata: {    retry_policy: "exponential_backoff",    max_retries: 3,    timeout: 300000, // 5 minutes    on_failure: "notify_and_rollback"  }})

mcp__flow-nexus__workflow_create({  name: "Resilient Workflow",  steps: [...],  metadata: {    retry_policy: "exponential_backoff",    max_retries: 3,    timeout: 300000, // 5 minutes    on_failure: "notify_and_rollback"  }})

4. Monitor and Scale

javascript

// Regular monitoringconst status = await mcp__flow-nexus__swarm_status()
// Scale based on workloadif (status.workload > 0.8) {  await mcp__flow-nexus__swarm_scale({ target_agents: status.agents + 2 })}

// Regular monitoringconst status = await mcp__flow-nexus__swarm_status()
// Scale based on workloadif (status.workload > 0.8) {  await mcp__flow-nexus__swarm_scale({ target_agents: status.agents + 2 })}

5. Use Async Execution for Long-Running Workflows

javascript

// Long-running workflows should use message queuesmcp__flow-nexus__workflow_execute({  workflow_id: "data-pipeline",  async: true // Non-blocking execution})
// Monitor progressmcp__flow-nexus__workflow_queue_status({ include_messages: true })

// Long-running workflows should use message queuesmcp__flow-nexus__workflow_execute({  workflow_id: "data-pipeline",  async: true // Non-blocking execution})
// Monitor progressmcp__flow-nexus__workflow_queue_status({ include_messages: true })

6. Clean Up Resources

7. Leverage Templates

javascript

// Use proven templates instead of building from scratchmcp__flow-nexus__swarm_create_from_template({  template_name: "code-review",  overrides: { maxAgents: 4 }})

// Use proven templates instead of building from scratchmcp__flow-nexus__swarm_create_from_template({  template_name: "code-review",  overrides: { maxAgents: 4 }})

Integration with Claude Flow

Flow Nexus swarms integrate seamlessly with Claude Flow hooks:

bash

# Pre-task coordination setupnpx claude-flow@alpha hooks pre-task --description "Initialize swarm"
# Post-task metrics exportnpx claude-flow@alpha hooks post-task --task-id "swarm-execution"

# Pre-task coordination setupnpx claude-flow@alpha hooks pre-task --description "Initialize swarm"
# Post-task metrics exportnpx claude-flow@alpha hooks post-task --task-id "swarm-execution"

Common Use Cases

1. Multi-Repo Development

Coordinate development across multiple repositories
Synchronized testing and deployment
Cross-repo dependency management

2. Research Projects

Distributed information gathering
Parallel analysis of different data sources
Collaborative synthesis and reporting

3. DevOps Automation

Infrastructure as Code deployment
Multi-environment testing
Automated rollback and recovery

4. Code Quality Workflows

Automated code review
Security scanning
Performance benchmarking

5. Data Processing

Large-scale ETL pipelines
Real-time data transformation
Data validation and quality checks

Authentication & Setup

bash

# Install Flow Nexusnpm install -g flow-nexus@latest
# Register accountnpx flow-nexus@latest register
# Loginnpx flow-nexus@latest login
# Add MCP server to Claude Codeclaude mcp add flow-nexus npx flow-nexus@latest mcp start

# Install Flow Nexusnpm install -g flow-nexus@latest
# Register accountnpx flow-nexus@latest register
# Loginnpx flow-nexus@latest login
# Add MCP server to Claude Codeclaude mcp add flow-nexus npx flow-nexus@latest mcp start

Support & Resources

Platform: https://flow-nexus.ruv.io
Documentation: https://github.com/ruvnet/flow-nexus
Issues: https://github.com/ruvnet/flow-nexus/issues

Remember: Flow Nexus provides cloud-based orchestration infrastructure. For local execution and coordination, use the core claude-flow MCP server alongside Flow Nexus for maximum flexibility.

Source and attribution

Source:ruvnet/rufloin.claude/skills/flow-nexus-swarmat commit60de638

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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Flow Nexus Swarm

Flow Nexus Swarm & Workflow Orchestration

📋 Table of Contents

Overview

Swarm Management

Initialize Swarm

Spawn Agents

Orchestrate Tasks

Monitor & Scale Swarms

Workflow Automation

Create Workflow

Execute Workflow

Monitor Workflows

Agent Assignment

Queue Management

Agent Orchestration

Full-Stack Development Pattern

Research & Analysis Pattern

CI/CD Pipeline Pattern

Data Processing Pipeline Pattern

Templates & Patterns

Use Pre-built Templates

Custom Template Creation

Advanced Features

Real-time Monitoring

Swarm Metrics & Analytics

Multi-Swarm Coordination

Best Practices

1. Choose the Right Topology

2. Optimize Agent Assignment

3. Implement Proper Error Handling

4. Monitor and Scale

5. Use Async Execution for Long-Running Workflows

6. Clean Up Resources

7. Leverage Templates

Integration with Claude Flow

Common Use Cases

1. Multi-Repo Development

2. Research Projects

3. DevOps Automation

4. Code Quality Workflows

5. Data Processing

Authentication & Setup

Support & Resources

Source and attribution

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Cron Schedule

Autopilot Predict

Autopilot Loop

Worker Integration

Worker Benchmarks

Swarm Advanced

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Ppt Template Creator

Skill Development

Plugin Structure

Command Development

Claude Md Improver

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